Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data

Yingyan Zhao, Yihong Zhou and Wu Deng
Additional contact information
Yingyan Zhao: College of Business Administration, Ningbo Polytechnic, Ningbo 315800, China
Yihong Zhou: Office of Educational Administration, Ningbo Polytechnic, Ningbo 315800, China
Wu Deng: School of Software Engineering, Dalian Jiaotong University, Dalian 116028, China

Sustainability, 2020, vol. 12, issue 8, 1-13

Abstract: With the advent of big data era and rapid development of Internet technology, e-commerce has had a strong development tendency that causes many problems, such as redundant and complex business processes, low efficiency and a high cost for e-commerce logistics in the distribution sector. It is not difficult to conclude that the key to improving logistics distribution efficiency—and reduce logistics distribution costs—is to optimize logistics distribution under big data. In this study, the management model, influence factors and development status of B2C e-commerce logistics distribution under big data are analyzed in detail. Then big data processing, business process and route optimization strategies for B2C e-commerce logistics distribution under big data are deeply studied. Furthermore, an optimization model of product sales and logistics distribution of B2C e-commerce by big data platform is discussed in order to propose an innovative optimization strategy for B2C e-commerce logistics distribution under big data. Big data technology is applied in B2C e-commerce logistics business management, which is studied in detail. These findings achieve the optimal distribution of B2C e-commerce, reduce the B2C e-commerce logistics distribution cost and improve the B2C e-commerce logistics distribution efficiency under big data. In addition, enhanced competitiveness of B2C e-commerce logistics distribution is examined in this study. This study provides a reference for follow-up big data studies in the field of e-commerce.

Keywords: B2C e-commerce; logistics distribution; Big data; optimization strategy; innovative model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/8/3381/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/8/3381/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:8:p:3381-:d:348402

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().